大破坏
发表于 2025-3-21 19:33:17
书目名称Database Systems for Advanced Applications影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0284468<br><br> <br><br>书目名称Database Systems for Advanced Applications影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0284468<br><br> <br><br>书目名称Database Systems for Advanced Applications网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0284468<br><br> <br><br>书目名称Database Systems for Advanced Applications网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0284468<br><br> <br><br>书目名称Database Systems for Advanced Applications被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0284468<br><br> <br><br>书目名称Database Systems for Advanced Applications被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0284468<br><br> <br><br>书目名称Database Systems for Advanced Applications年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0284468<br><br> <br><br>书目名称Database Systems for Advanced Applications年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0284468<br><br> <br><br>书目名称Database Systems for Advanced Applications读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0284468<br><br> <br><br>书目名称Database Systems for Advanced Applications读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0284468<br><br> <br><br>
消极词汇
发表于 2025-3-21 23:12:36
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懦夫
发表于 2025-3-22 02:17:28
Higher-Order Graph Contrastive Learning for Recommendationom the original graph to enhance supervisory signals. Specifically, we construct two contrasting views: higher-order and general views. In the higher-order view, we devise a high-order symmetric contrastive scheme to better explore higher-order dependencies. For the general view, the objective is to
植物群
发表于 2025-3-22 06:53:25
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Individual
发表于 2025-3-22 11:44:43
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转折点
发表于 2025-3-22 13:39:06
Multi-level Contrastive Learning on Weak Social Networks for Information Diffusion Predictionn. To facilitate user representation learning under sparse labels and insufficient features, we further propose self-supervised training specifically tailored for social networks with weak information. In the second stage, the cascade representations are learned using the multi-head self-attention n
转折点
发表于 2025-3-22 17:17:11
BiasRec: A General Bias-Aware Social Recommendation Model initially constructs a bias matrix for each user and item, calculates bias scores, and removes them from the raw rating data. Subsequently, the debiased data is fed into a GNN to learn users’ genuine preferences. Last, it reasonably combines biases and preferences to make predictions. We performed
生存环境
发表于 2025-3-23 01:01:38
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激怒某人
发表于 2025-3-23 03:12:28
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利用
发表于 2025-3-23 09:09:00
Learning Social Graph for Inactive User Recommendationring model training, which improves the construction of new edges for inactive users. Extensive experiments on real-world datasets demonstrate that LSIR achieves significant improvements of up to 129.58% on NDCG in inactive user recommendation. Our code is available at ..